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A one‐year's worth of near‐global marine shallow single‐layer cloud top radiative cooling (CTRC) is derived from a radiative transfer model with inputs from the satellite cloud retrievals and reanalysis sounding. The mean cloud top radiative flux divergence is 61 Wm−2, decomposed into the longwave and shortwave components of 73 and −11 W m−2, respectively. Equatorward of 30°N/S, the CTRC is largely a reflection of free‐atmospheric specific humidity distribution: a dry atmosphere enhances CTRC by reducing downward thermal radiation. Consequently, the cooling minimizes in the "wet" tropics and maximizes in the "dry" eastern subtropics. Poleward of 30°N/S, the CTRC decreases slightly due to the colder clouds that emit less effectively. The CTRC exhibits distinctive seasonal cycles with stronger cooling in the winter and has amplitudes of order 10–20 Wm−2 in stratocumulus‐rich regions. The datasets were used to train a machine‐learning model that substantially speeds up the retrieval. Plain Language Summary: Marine low‐lying clouds cool by emitting thermal radiation. The cooling is known as cloud top radiative cooling (CTRC). A change in CTRC can influence the properties of marine clouds via many avenues, ranging from altering the vertical motions of the clouds to changing the clouds' ability to reflect sunlight. Despite the importance of CTRC to the climate system, its climatological characteristics, namely how it varies with space and time, remain unknown. This work fills this knowledge gap. We generate the product of the CTRC over the global ocean using a novel satellite methodology developed in our previous work. Analyses of the data show that the spatial and temporal distributions of the CTRC are largely reflections of the atmospheric humidity: the drier the atmosphere, the stronger the cooling. As a result, the CTRC is weakest in the wet tropics and strongest in the dry eastern subtropical oceans, such as the west of California coast. We also use the CTRC data to train a machine‐learning algorithm that can substantially speed up the calculation of CTRC. Key Points: A one‐year's worth of global marine shallow single‐layer cloud top radiative cooling (CTRC) is derived from satellite and reanalysis dataSpatial and seasonal variations of CTRC are largely reflections of changes in free‐tropospheric humidity and cloud top temperatureA neural network model for the CTRC was trained, which substantially speeds up the retrieval while maintaining good accuracy [ABSTRACT FROM AUTHOR]

Summary: An urban energy and water balance model is presented which uses a small number of commonly measured meteorological variables and information about the surface cover. Rates of evaporation-interception for a single layer with multiple surface types (paved, buildings, coniferous trees and/or shrubs, deciduous trees and/or shrubs, irrigated grass, non-irrigated grass and water) are calculated. Below each surface type, except water, there is a single soil layer. At each time step the moisture state of each surface is calculated. Horizontal water movements at the surface and in the soil are incorporated. Particular attention is given to the surface conductance used to model evaporation and its parameters. The model is tested against direct flux measurements carried out over a number of years in Vancouver, Canada and Los Angeles, USA. At all measurement sites the model is able to simulate the net all-wave radiation and turbulent sensible and latent heat well (RMSE=25–47Wm−2, 30–64 and 20–56Wm−2, respectively). The model reproduces the diurnal cycle of the turbulent fluxes but typically underestimates latent heat flux and overestimates sensible heat flux in the day time. The model tracks measured surface wetness and simulates the variations in soil moisture content. It is able to respond correctly to short-term events as well as annual changes. The largest uncertainty relates to the determination of surface conductance. The model has the potential be used for multiple applications; for example, to predict effects of regulation on urban water use, landscaping and planning scenarios, or to assess climate mitigation strategies. [ABSTRACT FROM AUTHOR]

new method to estimate tree biomass heat storage from thermal infrared (TIR) imaging of biomass surface temperature is presented. TIR images of the canopy are classified into trunk, branches, and leaves. The one-dimensional heat equation in cylindrical coordinates is forced with trunk and branch surface temperatures to simulate the temperature distribution and heat storage in tree trunks and branches. Assuming uniform leaf temperatures, heat storage in leaves is computed from the surface temperature of the leaves separately for the sunlit upper and shaded lower canopy. The sum of trunk, branches, leaf, and air heat storage gives the canopy heat storage. Measurements in a walnut orchard near Davis, California, in early June 2007 showed that biomass heat storage was of the same order as air heat storage and about 1% of daytime and 9% of nighttime net radiation. [ABSTRACT FROM AUTHOR]

In this work, some sea viewing wide field-of-view sensor (SeaWiFS) images over the Santa Barbara Channel (SBC) are analysed. Pixel-by-pixel measurements of radiances at eight SeaWiFS channels and analytic Jacobians are simulated using a coupled atmosphere-ocean radiative transfer model. The inverse algorithm is based on optimal estimation with loosely constrained a priori data. The five-element state vector has two aerosol (optical depth at 865 nm, bimodal fraction of particles) and three marine (chlorophyll concentration, detrital/dissolved-matter absorption at 443 nm, and backscattering coefficient at 443 nm) parameters. The retrieval is stable and well posed; the results are smoother and show less spread than those derived from the standard SeaDAS v4.8 algorithm. For a 28 February 2003 SeaWiFS image, the average radiance residual is less than 1% for seven SeaWiFS channels, and less than 2% for the 765 nm channel. For a series of SBC SeaWiFS match-up cases over a 4-year period, estimated water-leaving radiances agree well with field measurements. [ABSTRACT FROM AUTHOR]

Abstract: A numerical model for cooling and welding of ash-flow tuffs was developed to obtain a quantitative understanding of the welding compaction that occurs during the cooling of ash-flow sheets and to evaluate the relative effects of emplacement temperature, thickness, and emplacement histories on compaction zonation (density profiles) of large ash-flow sheets. This model includes a set of two-phase, compressible Navier–Stokes equations for the transport of mass, momentum, and energy for a variable density volatile outfluxing through a porous media (ash-flow tuff). With this model we calculated theoretical compaction profiles (density vs. elevation) to match actual data measured in sections of Bishop Tuff. Compaction profiles from the Adobe basin indicate that there were 3 periods of non-deposition (5, 10, and 40 days) separating 4 distinct rapidly emplaced packets (REP) of pyroclastic flow deposition. In contrast, the 3 periods of quiescence (400, 20, and 800 days) between the 4 REPs in Chidago Canyon were considerably longer. These data constrain models of eruption for the Bishop Tuff by implying an eruption cycle that lasted longer than 3 years. The average calculated deposition temperatures for all 4 REPs in the Adobe basin are fairly uniform at 667±33 °C. In Chidago Canyon two of the REPs had a higher deposition temperature (∼660 °C) than the other two (534 °C). [Copyright &y& Elsevier]

The article focuses on a study by ecologist Ken Caldeira of Carnegie Institution of Washington in Stanford, California, which shows that temperate and high latitude forests have little to do with global mean temperature. It is widely believed that planting temperate trees would reduce temperature. According to Caldeira, any cooling from carbon absorption by these trees is balanced by warming from their absorption of solar radiation. Caldeira feels that relying solely on reduced atmospheric carbon in temperate forest will not address the problem of global warming.

This article presents information on an infinitesimal radiation measuring instrument installed at Mount Wilson observatory in Pasadena, California. The instrument can measure the radiation of heat from 124 stars with very small heat differences as one millionth of a degree centigrade. This wonder of science is one thousandth of a water droplet in size and weighs one thirtieth of a milligram.